Compression and decoding of single sensor color image data

ABSTRACT

A method is described to greatly improve the efficiency of and reduce the complexity of image compression when using single-sensor color imagers for video acquisition. The method in addition allows for this new image compression type to be compatible with existing video processing tools, improving the workflow for film and television production.

PRIORITY AND RELATED APPLICATIONS

This application is a continuation of and claims the benefit of priorityto U.S. patent application Ser. No. 16/234,389 entitled “COMPRESSION ANDDECODING OF SINGLE SENSOR COLOR IMAGE DATA”, filed Dec. 27, 2018, issuedas U.S. Pat. No. 10,574,898 on Feb. 25, 2020, which is a continuation ofand claims the benefit of priority to U.S. patent application Ser. No.15/654,532 of the same title, filed on Jul. 19, 2017, now issued as U.S.Pat. No. 10,212,352, which is a continuation of and claims the benefitof priority to U.S. patent application Ser. No. 15/215,397 of the sametitle, filed Jul. 20, 2016, now issued as U.S. Pat. No. 9,736,384, whichis a continuation of and claims the benefit of priority to U.S. patentapplication Ser. No. 14/676,776 of the same title, filed Apr. 1, 2015,now issued as U.S. Pat. No. 9,438,799, which is a continuation of andclaims the benefit of priority to U.S. patent application Ser. No.14/504,326 of the same title, filed Oct. 1, 2014, now issued as U.S.Pat. No. 9,025,896, which is a continuation of and claims the benefit ofpriority to U.S. patent application Ser. No. 14/222,549 of the sametitle, filed Mar. 21, 2014, now issued as U.S. Pat. No. 8,879,861, whichis a continuation of and claims the benefit of priority to U.S. patentapplication Ser. No. 14/108,240 of the same title, filed Dec. 16, 2013,now issued as U.S. Pat. No. 8,718,390, which is a continuation of andclaims the benefit of priority to U.S. patent application Ser. No.13/968,423 of the same title, filed Aug. 15, 2013, now issued as U.S.Pat. No. 8,644,629, which is a continuation of and claims the benefit ofpriority to U.S. patent application Ser. No. 13/683,965 of the sametitle, filed Nov. 21, 2012, now issued as U.S. Pat. No. 8,538,143, whichis a continuation of and claims the benefit of priority to U.S. patentapplication Ser. No. 13/196,175 entitled “METHOD FOR EFFICIENTCOMPRESSION AND DECODING OF SINGLE SENSOR COLOR IMAGE DATA”, filed Aug.2, 2011, now issued as U.S. Pat. No. 8,345,969, which is a continuationof and claims the benefit of priority to U.S. patent application Ser.No. 11/689,975 entitled “METHOD FOR EFFICIENT COMPRESSION AND DECODINGOF SINGLE SENSOR COLOR IMAGE DATA”, filed Mar. 22, 2007, now issued asU.S. Pat. No. 8,014,597, which claims the benefit of priority under 35U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No.60/784,866, entitled “EFFICIENT STORAGE AND EDITING OF HIGH RESOLUTIONSINGLE SENSOR COLOR VIDEO DATA,” filed Mar. 22, 2006, each of theforegoing being incorporated herein by reference in its entirety. Thisapplication is also related to U.S. patent application Ser. No.10/779,335, entitled “System and Method for Encoding and DecodingSelectively Retrievable Representations of Video Content,” filed Feb.12, 2004, the contents of which being incorporated herein by referencein its entirety.

FIELD OF THE ART

This present invention relates to compression and retrieval of videocontent gathered from a single-sensor imager.

BACKGROUND

Professional video cameras typically have three sensors to collectlight, each filtered for red, green, and blue channels. Digital stillphotography typically does not employ a three-sensor design; digitalstill photography instead uses a single sensor design with individualpixels filtered for red, green, and blue (or other color primaries suchas magenta, cyan and yellow.) This single-sensor color design issometimes called a Bayer sensor, which is common in nearly all digitalstill cameras, both professional and consumer models. As the spatialresolution of video increases, there are numerous benefits in switchingto the single-sensor Bayer design—as observed in some very high-enddigital cinema cameras used for movie acquisition. Yet traditionallythere are post-production workflow issues that arise when applying Bayersensors to video applications.

Notably, image data collected from Bayer-pattern imagers (also known asRAW images) is neither YUV nor RGB, the most common color orientationexpected by traditional post-production tools. This is true for bothstill cameras and emerging digital cinema cameras. This characteristicdemands that existing industry tools either be “upgraded” so they arecompatible with RAW images, or that new utilities be written thatconvert RAW images into traditional planar color spaces compatible withexisting industry tools. The most common workflow employed by theindustry today is to arithmetically convert RAW images into planar RGBimages before common operations are performed, such as applying asaturation matrix or white balance, which is then followed bycompressing or encoding the result into a smaller file size.

In order to extract full spatial and color information from a RAW image,a highly compute-intensive operation known as a “demosaic filter” mustfirst be applied to each RAW image. The demosaic operation interpolatesmissing color primaries at each pixel location, as Bayer sensors onlynatively provide one primary color value per pixel location. Theseoperations are generally performed by special algorithms residing insidethe camera. In this situation the RAW image is never presented to theuser, but instead the “developed” YUV or RGB image is presented to theuser from the camera after internal processing, sometimes in the form ofa compressed JPEG (or other compressed format) image. In the case of RAWmodes on digital still cameras, some camera processing is delayed andperformed outside the camera (most notably the compute-intensivedemosaic processing). In this case the unprocessed RAW image ispresented to the user from the camera, but prior to traditional YUV orRGB processing the demosaic (also known as de-Bayer) filter still mustfirst be applied to the RAW image, but is done so outside the camera,yet the processing order described remains the same. The “developed”output of the de-Bayer filter operation is a planar image, usually RGB,but may also be other color primaries instead. A filter to correct colorand contrast (compensating for sensor characteristics) is then appliedto the planar image. Typically the planar image color space is furtherconverted to a more compressible form such as YUV (common for DV, JPEG,or MPEG compression). The YUV image is compressed for delivery orstorage, whether inside the camera or performed as a second step outsidethe camera.

In the RAW mode, some digital still cameras allow preprocessed sensordata to be written to the file along with metadata describing thecameras settings. A still-camera RAW mode does not achieve the workflowbenefits described here, as it does not allow easy or fast previews, andthe images can only be displayed by tools designed to understand the RAWformat from Bayer-pattern imagers.

SUMMARY

Exemplary embodiments of the invention that are shown in the drawingsare summarized below. These and other embodiments are more fullydescribed in the detailed description section. It is to be understood,however, that there is no intention to limit the invention to the formsdescribed in this Summary of the Invention or in the detaileddescription. One skilled in the art can recognize that there arenumerous modifications, equivalents and alternative constructions thatfall within the spirit and scope of the invention as expressed in theclaims.

Embodiments of the invention describe systems and methods for effectingRAW Bayer compression using a camera by itself or an external devicethat performs the Bayer compression. In both cases this compressedstream is stored to a disk or memory system for later review andediting. During the review and editing stages, embodiments of theinvention enable the new compressed video type to operate seamlesslywithin existing post production tools, without modification to thosetools.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects and advantages plus a more complete understanding of theinvention are apparent and more readily appreciated by reference to thefollowing detailed description and to the appended claims when taken inconjunction with the accompanying drawings wherein:

FIG. 1 shows the primary color layout for a typical “Bayer” image sensorwhich consists of twice as many green cells/pixels as red or blue cells.These pixels or cells are most commonly arranged in a 2×2 pixel grid asshown here.

FIG. 2 shows the separation of the red and blue channel color primariesinto independent half-resolution channels.

FIG. 3 shows the separation of the green primary into two highlycorrelated channels.

FIG. 4A shows an alternative separation of the green primary into onechannel with reduced correlation, but still effective.

FIG. 4B shows an alternative separation of green into a single channelthat is highly correlated, but with an image shape that would requiremore advanced processing during compression.

FIG. 5A shows an implementation of green color summation, according toone embodiment.

FIG. 5B shows an implementation of red-green color differencing,according to one embodiment.

FIG. 5C shows an implementation of blue-green color differencing,according to one embodiment.

FIG. 5D shows an implementation of green color differencing, accordingto one embodiment.

FIG. 6 shows the pixels that are derived through de-Bayer filtering.

FIG. 7 shows an overview of Bayer compression for preview presentation.

FIG. 8 shows an overview of Bayer compression using color differencing.

DETAILED DESCRIPTION

The invention allows for video images from Bayer-style cameras to beprocessed in high resolution far more efficiently than the current stateof the art. The interleaved color components within a Bayer sensor aretypically arranged in 2×2 pixel squares over the entire image with redand green on the top pair, and green and blue on the bottom of each 2×2pixel array. This pattern of interleaved red, green and blue pixels isproblematic for compression as a single image because the spatiallyadjacent pixels are much less correlated and therefore less compressiblethan a plane of monochrome data. Compression operates most effectivelywhen adjacent pixels have a high likelihood of being similar, yet in aBayer image the adjacent pixels are filtered for different colorprimaries, so pixel magnitudes will vary greatly. Attempting directcompression of a Bayer image using common techniques such as DCT orwavelet compression will either result in little or no reduction of datasize, or a significant amount of image distortion. This invention allowshigher compression without introducing visually-damaging distortion ofthe image, using existing compression technologies like DCT and wavelet.

A single high definition Bayer frame of 1920×1080 interleaved red,green, and blue pixels can be separated into four planes ofquarter-resolution images, each consisting 960×540 pixels of either thered component, blue component, or one of the two green components. Ifred is the upper left pixel of the frame, a correlated red plane isfetched by reading every second pixel on every other scan-line. The sametechnique can be applied for all colors so that each plane contains thesignal for one color primary. For the most common RGGB Bayer patternimager, there are two green planes for each red and blue plane. It ispossible to encode each of the planes using common compressiontechniques (DCT, Wavelet, etc.) such that significant data reduction isachieved without significant quality impacts. However, more compressionmay be obtained by differencing the channels in the following manner:

G=green plane1+green plane2

R-G=2×red plane−G

B-G=2×blue plane−G

D=green plane1−green plane2 (D for difference between the green planes)

These modified image planes are encoded (e.g., compressed) just as theywould if they were separate planes of R, G and B, or Y, U and Vcomponents. Other planar differencing algorithms could be used todecrease the size of the compressed data output yielding a similarresult. Reordering the data into planes of the color primaries is notcompute intensive, and the operation is reversible. No data is added orlost as it is with de-Bayer processing.

De-Bayer filtering (or demosaicing) is the process of interpolating themissing color components at every pixel location. As acquired, the Bayersensor only collects one of the three color primaries at every pixelsite—the two other primaries are predicted via a range of differentalgorithms that typically take substantial compute time for high qualityresults. In the above 1920×1080 encoding example, the compressed videoimage produced will be smaller in data size yet higher in visual qualitythan results from existing techniques used in today's video cameras. Ifa Bayer image is to be compressed in a format like MPEG or HOV, thende-Bayering (a.k.a. demosaicing) will expand the single plane of1920×1080 pixel data into three 1920×1080 planes, one for each colorprimary. This increases the size of the data by 3×, and does not benefitthe compression (much larger compressed files result), and potentiallyintroduces visual artifacts depending on the choice of de-Bayer filterapplied (no de-Bayer algorithm is ideal). Although disadvantages (largerfile sizes and visual impairments) are clearly evident in this example,this is the standard approach used in single-sensor video cameras. Byencoding four quarter-resolution planes versus three full-resolutionplanes, the computational load is greatly reduced, allowing for simplerimplementations and longer camera battery life. The size of thecompressed data is reduced significantly, allowing for longer recordtimes or alternatively reduced storage requirements for the capturedvideo.

Although advantages for encoding four quarter-resolution planes areevident, the resulting compressed image would not be playable usingtypical hardware or software tools, as no viewing or editing toolsanticipate four quarter-resolution planes instead of threefull-resolution planes. A modification to the decompression algorithmwill solve this problem. By way of example, a traditional three-plane1920×1080 encoding would present a full-resolution 1920×1080 image upondecode. The codec, which is a combination of the compressor and thedecompressor, is just a black box to the viewer or editing tool. Codecsnormally are intended to precisely reproduce their input(s). In thisinvention, the decoder will change its default behavior depending on howit is being used, and modify its output as needed by the application.For fast preview/playback the decoder will reconstruct the image atquarter resolution of the source (in this example 960×540), and to dothis it only needs to decode Channel G, R-G and B-G to provide astandard RGB image to the requesting tool. As this is just for preview,the reconstructed RGB planes require no de-Bayer step to produce a goodquality video output. Further, decoding of three quarter-resolutionchannels is significantly faster than decoding three full-resolutionchannels, resulting in reduced costs of the player and editing system.The decreased resolution is of minor or no issue for previewapplications within post-production for film or television, and is infact an advantage in many situations, yet this would not be suitable fora live event where high-quality full-resolution decoding is neededimmediately (for live projects more traditional camera processing isbetter suited). Fortunately most video productions undergo a shotselection process and editing stage, which is one area where thisinvention is well-suited.

By way of example, a fast decode mode may perform the following methodoutlined in the following paragraphs. During the fast decode mode, onlythe necessary planes are decompressed. If the unmodified red, green1,green2, and blue planes were encoded, only one of the two green channelsneeds to be presented for preview. This selection of decoding three ofthe four channels offers additional performance. When color differencingis applied, the RGB planes would be reconstructed as follows:

Red plane=(R-G+G) divide 2

Green plane=G divide 2

Blue plane=(B-G+G) divide 2

The fourth channel of the two differenced green channels in not requiredfor a preview playback. The resulting three color primary channels canbe presented to the playback/editing application as a standardquarter-resolution image, even though those channels were originallyderived from a larger Bayer image. The slight spatial offset of eachcolor plane, such as red pixels being sampled from a slightly differentlocation than the blue or green pixels, does not present an issue forfast preview/playback. The image quality is high. The three colorchannels are typically interleaved in a RGBRGBRGB . . . format fordisplay. Each pixel now has the needed three primary colors for display.As an optional step, if the application can only support full resolution(versus quarter resolution), then using a simple bi-linear interpolationor pixel duplication may be performed by the decoder on thequarter-resolution image to quickly convert it to a full-resolution RGBimage. This operation is significantly faster than performing ahigh-quality demosaic filter in real time. For higher qualityfull-resolution presentation, the decoder performs de-Bayer filtering sothe post-production tools can manipulate a traditional full-resolutionimage. DeBayer filtering is slow because it is highly compute intensive,and certain embodiments of the invention allow transfer of theprocessing from the camera to the post-production stage at which pointthe processing is typically performed on powerful computer workstationsand is more suited to high-quality de-Bayer processing. Workflow alsogains efficiency through this change, For example, a film or televisionproduction will on average record 20 times the length of source footageas compared with the length of the edited product. In this example, atwo-hour movie will likely have 40 hours of source footage. Thecompute-expensive de-Bayer processing is now only needed on 5% on theacquired video because it is performed at the end of the workflowinstead of at the beginning. In addition, the review process to selectthis 5% of the video is now easier and faster because the data size andcomputational load are much smaller. This compares to more traditionalhandling of Bayer-format source data on which de-mosaic processing mustbe performed on 100% of the data before it is even viewable.

By way of a new example, a full-resolution decode mode may perform themethod outlined in the following paragraphs. During the full-resolutiondecode mode, all four quarter-resolution planes are decoded. Anycolor-plane differencing is reversed so that planes of red, green1,green2 and blue are restored. The resulting planes are interleaved backinto the original Bayer layout, and the result of the decode now matchesthe original source image. A de-Bayer operation is performed to convertthe image into a full raster RGB frame and this result is presented tothe calling application.

De-Bayer filters are typically non-linear filters designed withflexibility to offer a significant range of characteristics. Because ofthis, the style of de-Bayer filter may be selectable, either directly bythe user or automatically via the type of operation being performed bythe editing tools. As an example, the “export” mode from an NLE, whenthe result is intended to be transferred to film for viewing, would usethe highest quality de-Bayer filter, whereas scrubbing the timeline in anonlinear editor would use a simpler/faster filter).

One skilled in the art will recognize that, because the original videodata size is unwieldy, today's post-production world typically scaleshigh-resolution images to approximately one-quarter resolution to selectshots for editing. This technique is called “offline” editing. Once anoffline edit session is completed, a “conform” process is used to gatheronly the necessary full-resolution files (e.g., now 5% of thesource—although the large full-resolution files have to be archivedsomewhere) to complete the TV/feature production. Certain embodiments ofthe invention achieve much the same workflow without the expensive stepsof image scaling and conforming, and offer much smaller archival storagerequirements. This novel new workflow is further enhanced by allowingfull-resolution decodes whenever the editing/user needs, which is notpossible in offline editing. Switching between very fast preview-decodeand full-resolution de-Bayer output is made automatically in oneembodiment. For example, playback and review may use the fast decodemode, while single-frame review and export may be performed at fullresolution.

When the de-Bayer operation is not performed in the camera, the choicesfor post-production image enhancement are greatly improved. For example,the selection of the specific de-Bayer filter can be made afterpost-production when the edited material is exported to its finalpresentation format. A lower quality, but more efficient, de-Bayerfilter can be used for real-time preview during editing and a higherquality algorithm, which may be computationally slower, can be used forexport (e.g., to film or a digital presentation format). Workflow isimproved further because preprocessed sensor data is better foradjusting color characteristics such as white balance, contrast andsaturation during post-production.

Embodiments of the invention may be used to improve any existingcompression algorithm for encoding and decoding. No new compressiontechnologies are required to enable direct Bayer processing. Forexample, algorithms including DCT, wavelet, or others can be used. Thecompression can be lossy or lossless. The codec must decode to theformat used by the post-production tools, otherwise the tools would needto be updated to be aware of the new format. To maintain compatibilitywith the widest range of video applications the Bayer codec is wrappedin one or more of the standard media interfaces, such as QuickTime,DirectShow, Video for Windows, etc. These media interfaces allowexisting applications to gain support for new media types, withoutrequiring any internal knowledge of the media's structure. By using thestandard codec wrapper of these common media interfaces, even RAW datacan be presented to an application by developing the image to the formatrequirements of the calling application. Video cameras that offercodec-less (uncompressed) raw acquisition, and which do not abstract theformat through a codec wrapper, require special tools withinpost-production to convert this data into a more traditional form beforereview and editing can begin, introducing a cumbersome workflow.

Those skilled in the art can readily recognize that numerous variationsand substitutions may be made in the invention, its use and itsconfiguration to achieve substantially the same results as achieved bythe embodiments described herein. Accordingly, there is no intention tolimit the invention to the disclosed exemplary forms. Many variations,modifications and alternative constructions fall within the scope andspirit of the disclosed invention as expressed in the claims.

What is claimed is:
 1. A computerized apparatus configured to processimage data, comprising: a sensor; a processor; and a non-transitorycomputer-readable medium in data communication with the processor, thenon-transitory computer-readable medium comprising instructions that,when executed by the processor, cause the processor to: obtain afull-resolution Bayer image data frame from the sensor, where thefull-resolution Bayer image data frame comprises first pixelscorresponding to a first color, second pixels corresponding to a secondcolor, and third pixels corresponding to a third color, and where thefirst pixels, the second pixels, and the third pixels of thefull-resolution Bayer image data frame are interleaved; prior to ademosaic process, process the full-resolution Bayer image data frameinto at least a first fractional-resolution image data portioncomprising the first pixels corresponding to the first color, at leastone second fractional-resolution image data portion comprising thesecond pixels corresponding to the second color, and a thirdfractional-resolution image data portion comprising the third pixelscorresponding to the third color; and form image data channels based onat least two of: the first fractional-resolution image data portion, theat least one second fractional-resolution image data portion, and thethird fractional-resolution image data portion.
 2. The computerizedapparatus of claim 1, where the instructions, when executed by theprocessor, are further configured to cause the processor to perform thedemosaic process on at least a portion of image data channels, thedemosaic process comprising at least a de-Bayer operation.
 3. Thecomputerized apparatus of claim 2, where the instructions, when executedby the processor, are further configured to cause the processor toperform an algorithmic compression operation on at least the portion ofthe image data channels to produce compressed image data.
 4. Thecomputerized apparatus of claim 3, where the algorithmic compressionoperation produces the compressed image data from different combinationsof: the first pixels corresponding to the first color, the second pixelscorresponding to the second color; or the third pixels corresponding tothe third color.
 5. The computerized apparatus of claim 4, where thealgorithmic compression operation comprises a variable lengthcompression; at least a first compressed image data has a first lengthdifferent than a second compressed image data with a second length; andwhere the first compressed image data and the second compressed imagedata are associated with the full-resolution Bayer image data frame. 6.The computerized apparatus of claim 5, where: the first color comprisesa red color; the at least one second fractional-resolution image dataportion comprises a first plane of second pixels and a second plane ofsecond pixels corresponding to a green color; the third color comprisesa blue color; and the compressed image data comprises: a red color/greencolor difference data; at least one mathematical combination of thefirst plane of second pixels and the second plane of second pixelscorresponding to the green color; and a blue color/green colordifference data.
 7. The computerized apparatus of claim 1, furthercomprising a battery power supply; and where processing thefull-resolution Bayer image data frame into the firstfractional-resolution image data portion, the at least one secondfractional-resolution image data portion, and the thirdfractional-resolution image data portion, reduces computational load andallows for a longer battery life compared to processing a plurality offull-resolution planes from the full-resolution Bayer image data frame.8. The computerized apparatus of claim 1, further comprising a datastorage device; and where the image data channels consume less storagespace within the data storage device than a plurality of full-resolutionplanes obtained from the full-resolution Bayer image data frame.
 9. Thecomputerized apparatus of claim 1, where the instructions, when executedby the processor, are further configured to cause the processor togenerate a preview from only a subset of the image data channels. 10.The computerized apparatus of claim 9, where each of the image datachannels correspond to a different combination of: the firstfractional-resolution image data portion, the at least one secondfractional-resolution image data portion, and the thirdfractional-resolution image data portion; the at least one secondfractional-resolution image data portion comprises a first plane ofsecond pixels and a second plane of second pixels; the first colorcomprises a red color, the second color comprises a green color, and thethird color comprises a blue color; and the image data channelscomprise: a red color/green color difference data; at least onemathematical combination of the first plane of second pixels and thesecond plane of second pixels corresponding to the green color; and ablue color/green color difference data.
 11. A processor apparatusconfigured to process image data obtained from a sensor, comprising: aprocessor; and a non-transitory computer-readable medium in datacommunication with the processor, the non-transitory computer-readablemedium comprising instructions that, when executed by the processor,cause the processor to: obtain a full-resolution image data framecomprising first pixels corresponding to a first color, second pixelscorresponding to a second color, and third pixels corresponding to athird color, and where the first pixels, the second pixels, and thethird pixels of the full-resolution image data frame are interleaved;prior to any demosaic process, process the full-resolution image dataframe into at least a first fractional-resolution image data portioncomprising the first pixels, at least one second fractional-resolutionimage data portion comprising the second pixels, and a thirdfractional-resolution image data portion comprising the third pixels;and compress the first fractional-resolution image data portion, the atleast one second fractional-resolution image data portion, and the thirdfractional-resolution image data portion into compressed image data. 12.The processor apparatus of claim 11, where the sensor comprises a Bayersensor that provides one color value per pixel location; and thefull-resolution image data frame comprises RAW or Bayer-pattern imagedata.
 13. The processor apparatus of claim 11, where the compressedimage data correspond to different combinations of: the first pixelscorresponding to the first color, the second pixels corresponding to thesecond color; or the third pixels corresponding to the third color. 14.The processor apparatus of claim 13, further comprising instructionsthat, when executed by the processor, cause the processor to demosaiconly a subset of the compressed image data to generate anon-full-resolution image.
 15. The processor apparatus of claim 14,further comprising instructions that, when executed by the processor,cause the processor to filter the non-full-resolution image to correctfor at least one of color or contrast.
 16. The processor apparatus ofclaim 15, further comprising instructions that, when executed by theprocessor, cause the processor to: convert the non-full-resolution imageto YUV data; and compress the YUV data to produce compressed YUV data.17. The processor apparatus of claim 11, where the compressed image dataare based on a discrete cosine transform (DCT) or wavelet transform ofat least one of: the first fractional-resolution image data portion, theat least one second fractional-resolution image data portion, and thethird fractional-resolution image data portion.
 18. The processorapparatus of claim 11, further comprising instructions that, whenexecuted by the processor, cause the processor to: generate differencechannels from the first fractional-resolution image data portion, the atleast one second fractional-resolution image data portion, and the thirdfractional-resolution image data portion; and generate a preview basedon only a subset of the difference channels.
 19. The processor apparatusof claim 11, where the compression comprises a variable lengthcompression; at least a first compressed image data has a first lengthdifferent than a second compressed image data with a second length; andwhere the first compressed image data and the second compressed imagedata are associated with the full-resolution image data frame.
 20. Theprocessor apparatus of claim 11, where the sensor comprises a pluralityof pixel arrays comprising one of the first pixels, at least one of thesecond pixels, and one of the third pixels.
 21. The processor apparatusof claim 20, where: the plurality of pixel arrays each comprise a 2×2array; the first color comprises a red color; the second color comprisesa green color; the second pixels comprise first green pixels that arediagonally arranged relative to corresponding second green pixels; thethird color comprises a blue color; and the at least one secondfractional-resolution image data portion comprises a first greenfractional-resolution image data portion based on the first greenpixels, and a second green fractional-resolution image data portionbased on the second green pixels.
 22. A non-transitory computer-readablemedium in data communication with a processor, the non-transitorycomputer-readable medium comprising instructions that, when executed bythe processor, cause the processor to: obtain image data channels thatencode at least two of: a first fractional-resolution image data portionof a full-resolution image, at least one second fractional-resolutionimage data portion of the full-resolution image, and a thirdfractional-resolution image data portion of the full-resolution image;where the first fractional-resolution image data portion is associatedwith a first color, the at least one second fractional-resolution imagedata portion is associated with a second color, and the thirdfractional-resolution image data portion is associated with a thirdcolor; reconstruct the first fractional-resolution image data portion,the at least one second fractional-resolution image data portion, andthe third fractional-resolution image data portion based on at least onecolor differencing operation of the image data channels; and generate areduced-resolution image based on the first fractional-resolution imagedata portion, the at least one second fractional-resolution image dataportion, and the third fractional-resolution image data portion.
 23. Thenon-transitory computer-readable medium of claim 22, where the imagedata channels comprise different combinations of at least two of thefirst fractional-resolution image data portion, the at least one secondfractional-resolution image data portion, and the thirdfractional-resolution image data portion.
 24. The non-transitorycomputer-readable medium of claim 22, where the reduced-resolution imageis generated from the first fractional-resolution image data portion,the at least one second fractional-resolution image data portion, andthe third fractional-resolution image data portion, without ademosaicing process.
 25. The non-transitory computer-readable medium ofclaim 22, where the full-resolution image comprises RAW format data; andwhere the non-transitory computer-readable medium further comprisesinstructions that, when executed by the processor, cause the processorto provide the reduced-resolution image to a software process whichcannot read or utilize RAW data.